Breast cancer diagnosis and treatment can have a profound influence on a woman's physical, psychosocial, and overall well-being. We examined the prevalence of depressive symptoms and its association with health-related quality of life (HRQOL) in women who are survivors of breast cancer. We also assessed if factors, including metastasis, cancer recurrence, diagnosis of new primary cancers, and comorbid conditions, are associated with depressive symptoms.
The Patient Health Questionnaire (PHQ-8) and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 were mailed to assess depressive symptoms and HRQOL, respectively, in breast cancer patients who received cancer treatment in a large tertiary cancer center.
Two hundred forty patients participated (56% response rate and 6–13 years since treatment). The mean score on the PHQ-8 scale was 4 points (standard deviation [SD] 4.8, median 2.0). Sixteen percent had PHQ-8 score ≥10 and were categorized as depressed. Depression was inversely associated with HRQOL subscales for functioning, financial, and global health and positively associated with symptoms. Logistic regression showed that younger age (odds ratio [OR] age in years 0.92, 95% confidence interval [CI] 0.86- 0.99, p<0.02), rheumatoid arthritis (OR 8.4, 95%CI 1.3-57.4, p<0.03), and years from treatment (OR 0.70, 95% CI 0.46-0.99, p<0.05) were significant correlates of depression.
Depression is a significant health concern for breast cancer survivors and is associated with lower HRQOL. The results suggest the need to monitor women with breast cancer for depression and provide resources for treating depression during the survival period.
Effective management of symptoms in cancer patients requires early intervention. We assessed whether the timing of referral to the Supportive Care Center (SCC) and symptom burden outcome varied by race or ethnicity in lung cancer patients who had been seen at a tertiary cancer center.
Non-Hispanic white (n=752), Hispanic (n=111) and non-Hispanic black (n=117) patients with non-small cell lung cancer comprised our sample. Data on sociodemographic factors, stage of disease, comorbid conditions, and symptom severity (pain, depressed mood, fatigue) served as potential predictor variables.
While the mean time (15 months; median=7 months) from initial presentation at the cancer center to referral to the SCC did not vary by race or ethnicity, we found that Hispanics and non-Hispanic blacks had higher symptom burden when they first presented at the cancer center than non-Hispanic whites. Severe pain, depressed mood, and fatigue were significant predictors for early referral (< 7 months) of non-Hispanic whites, but only severe fatigue (P < 0.05) was predictive of early referral for Hispanics and non-Hispanic blacks. Furthermore, while the proportion of non-Hispanic white patients reporting severe pain, depressed mood, and fatigue significantly decreased (P < 0.001) at first follow-up visit after referral to the SCC; among Hispanics, improvement was only observed for depressed mood. No improvement in any of these symptoms was observed for non-Hispanic blacks.
While the timing of referral to supportive services did not vary by race, disparities in symptom burden outcomes persist. Additional studies are needed to validate our findings.
Folate metabolism, with its importance to DNA repair, provides a promising region for genetic investigation of lung cancer risk. This project investigates genes (MTHFR, MTR, MTRR, CBS, SHMT1, TYMS), folate metabolism related nutrients (B vitamins, methionine, choline, and betaine) and their gene-nutrient interactions.
We analyzed 115 tag single nucleotide polymorphisms (SNPs) and 15 nutrients from 1239 and 1692 non-Hispanic white, histologically-confirmed lung cancer cases and controls, respectively, using stochastic search variable selection (a Bayesian model averaging approach). Analyses were stratified by current, former, and never smoking status.
Rs6893114 in MTRR (odds ratio [OR] = 2.10; 95% credible interval [CI]: 1.20–3.48) and alcohol (drinkers vs. non-drinkers, OR = 0.48; 95% CI: 0.26–0.84) were associated with lung cancer risk in current smokers. Rs13170530 in MTRR (OR = 1.70; 95% CI: 1.10–2.87) and two SNP*nutrient interactions [betaine*rs2658161 (OR = 0.42; 95% CI: 0.19–0.88) and betaine*rs16948305 (OR = 0.54; 95% CI: 0.30–0.91)] were associated with lung cancer risk in former smokers. SNPs in MTRR (rs13162612; OR = 0.25; 95% CI: 0.11–0.58; rs10512948; OR = 0.61; 95% CI: 0.41–0.90; rs2924471; OR = 3.31; 95% CI: 1.66–6.59), and MTHFR (rs9651118; OR = 0.63; 95% CI: 0.43–0.95) and three SNP*nutrient interactions (choline*rs10475407; OR = 1.62; 95% CI: 1.11–2.42; choline*rs11134290; OR = 0.51; 95% CI: 0.27–0.92; and riboflavin*rs8767412; OR = 0.40; 95% CI: 0.15–0.95) were associated with lung cancer risk in never smokers.
This study identified possible nutrient and genetic factors related to folate metabolism associated with lung cancer risk, which could potentially lead to nutritional interventions tailored by smoking status to reduce lung cancer risk.
We, and others, have shown that experimenting with cigarettes is a function of both non-genetic and genetic factors. In this analysis we ask: how much of the total risk of experimenting with cigarettes, among those who had not experimented with cigarettes when they enrolled in a prospective cohort, is attributable to genetic factors and to non-genetic factors?
Participants (N = 1,118 Mexican origin youth), recruited from a large population-based cohort study in Houston, Texas, provided prospective data on cigarette experimentation over three years. Non-genetic data were elicited twice – baseline and follow-up. Participants were genotyped for 672 functional and tagging variants in the dopamine, serotonin and opioid pathways.
In the overall model, the adjusted combined non-genetic PAF was 71.2% and the adjusted combined genetic PAF was 58.5%. Among committed never smokers the adjusted combined non-genetic PAF was 67.0% and the adjusted combined genetic PAF was 53.5%. However, among cognitively susceptible youth, the adjusted combined non-genetic PAF was 52.0% and the adjusted combined genetic PAF was 68.4%.
Our results suggest there may be differences in genotypes between youth who think they will try cigarettes in the future compared to their peers who think they will not and underscore the possibility that the relative influence of genetic vs. non-genetic factors on the uptake of smoking may vary between these two groups of youth.
A clearer understanding of the relative role of genetic vs. non-genetic factors in the uptake of smoking may have implications for the design of prevention programs.
Growing evidence suggests that single nucleotide polymorphisms (SNPs) in nucleotide excision repair (NER) pathway genes play an important role in bladder cancer etiology. However, only a limited number of genes and variations in this pathway have been evaluated to date.
In this study, we applied a comprehensive pathway-based approach to assess the effects of 207 tagging and potentially functional SNPs in 26 NER genes on bladder cancer risk using a large case-control study consisting of 803 bladder cancer cases and 803 controls.
A total of 17 SNPs were significantly associated with altered bladder cancer risk at P<0.05, of which 7 SNPs retained noteworthiness after assessed by a Bayesian approach for the probability of false discovery. The most noteworthy SNP was rs11132186 in ING2 gene. Compared to the major allele-containing genotypes, the odds ratio (OR) was 0.52 (95% confidence interval [CI] 0.32–0.83, P = 0.005) for the homozygous variant genotype. Three additional ING2 variants also exhibited significant associations with bladder cancer risk. Significant gene-smoking interactions were observed for three of the top 17 SNPs. Furthermore, through an exploratory classification and regression tree (CART) analysis, we identified potential gene-gene interactions.
We conducted a large association study of NER pathway with bladder cancer risk and identified several novel predisposition variants. We identified potential gene-gene and gene-environment interactions in modulating bladder cancer risk. Our results reinforce the importance of a comprehensive pathway-focused and tagging SNP-based candidate gene approach to identify low-penetrance cancer susceptibility loci.
bladder cancer; genetic susceptibility; nucleotide excision repair; SNP; gene-smoking interaction
Established psychosocial risk factors increase the risk for experimentation among Mexican-origin youth. Now we comprehensively investigate the added contribution of select polymorphisms in candidate genetic pathways associated with sensation seeking, risk taking, and smoking phenotypes to predict experimentation.
Participants, (N=1,118 Mexican origin youth) recruited from a large population-based cohort study in Houston, Texas, provided prospective data on cigarette experimentation over three years. Psychosocial data were elicited twice—baseline and final follow-up. Participants were genotyped for 672 functional and tagging variants in the dopamine, serotonin and opioid pathways.
After adjusting for gender and age, with a Bayesian False Discovery Probability set at 0.8 and prior probability of 0.05, six gene variants were significantly associated with risk of experimentation. After controlling for established risk factors, multivariable analyses revealed that participants with six or more risk alleles were 2.25 (95%CI: 1.62–3.13) times more likely to have experimented since baseline compared to participants with five or fewer. Among committed never smokers (N=872), three genes (OPRM1, SNAP25, HTR1B) were associated with experimentation as were all psychosocial factors. Among susceptible youth (N=246) older age at baseline, living with a smoker, and three different genes (HTR2A, DRD2, SLC6A3) predicted experimentation.
Our findings, which have implications for development of culturally-specific interventions, need to be validated in other ethnic groups.
These results suggest that variations in select genes interact with a cognitive predisposition toward smoking. In susceptible adolescents, the impact of the genetic variants appears to be larger compared to committed never smokers.
Hypersensitivity to radiation exposure has been suggested to be a risk factor for the development of breast cancer. In this case–control study of 515 young women (≤55 years) with newly diagnosed sporadic breast cancer and 402 cancer-free controls, we examined the radiosensitivity as measured by the frequency of chromatid breaks induced by gamma-radiation exposure in the G2 phase of phytohemagglutinin-stimulated and short-term cultured fresh lymphocytes. We found that the average chromatid breaks per cell from 50 well-spread metaphases were statistically significantly higher in 403 non-Hispanic White breast cancer patients (0.52 ± 0.22) than that in 281 non-Hispanic White controls (0.44 ± 0.16) (P value < 0.001), and in 60 Mexican American breast cancer patients (0.52 ± 0.19) than that in 65 Mexican American controls (0.44 ± 0.16) (P value = 0.021), but the difference was not significant in African Americans (52 cases [0.45 ± 0.16] versus 56 controls [0.47 ± 0.16], P = 0.651). The frequency of chromatid breaks per cell above the median of control subjects was associated with two-fold increased risk for breast cancer in non-Hispanic Whites and Mexican Americans. A dose–response relationship was evident between radiosensitivity and risk for breast cancer (Ptrend < 0.001) in these two ethnic groups. We concluded that gamma-ray-induced mutagen sensitivity may play a role in susceptibility to breast cancer in young non-Hispanic White and Mexican American women.
Radiation; Chromosomal instability; Breast neoplasm; Molecular epidemiology
Gliomas, which generally have a poor prognosis, are the most common primary malignant brain tumors in adults. Recent genome-wide association studies have demonstrated that inherited susceptibility plays a role in the development of glioma. Although first-degree relatives of patients exhibit a two-fold increased risk of glioma, the search for susceptibility loci in familial forms of the disease has been challenging because the disease is relatively rare, fatal, and heterogeneous, making it difficult to collect sufficient biosamples from families for statistical power. To address this challenge, the Genetic Epidemiology of Glioma International Consortium (Gliogene) was formed to collect DNA samples from families with two or more cases of histologically confirmed glioma. In this study, we present results obtained from 46 U.S. families in which multipoint linkage analyses were undertaken using nonparametric (model-free) methods. After removal of high linkage disequilibrium SNPs, we obtained a maximum nonparametric linkage score (NPL) of 3.39 (P=0.0005) at 17q12–21.32 and the Z-score of 4.20 (P=0.000007). To replicate our findings, we genotyped 29 independent U.S. families and obtained a maximum NPL score of 1.26 (P=0.008) and the Z-score of 1.47 (P=0.035). Accounting for the genetic heterogeneity using the ordered subset analysis approach, the combined analyses of 75 families resulted in a maximum NPL score of 3.81 (P=0.00001). The genomic regions we have implicated in this study may offer novel insights into glioma susceptibility, focusing future work to identify genes that cause familial glioma.
Glioma; family studies; linkage; haplotype pattern; NPL
We recently proposed a bias correction approach to evaluate accurate estimation of the odds ratio (OR) of genetic variants associated with a secondary phenotype, in which the secondary phenotype is associated with the primary disease, based on the original case-control data collected for the purpose of studying the primary disease. As reported in this communication, we further investigated the type I error probabilities and powers of the proposed approach, and compared the results to those obtained from logistic regression analysis (with or without adjustment for the primary disease status). We performed a simulation study based on a frequency-matching case-control study with respect to the secondary phenotype of interest. We examined the empirical distribution of the natural logarithm of the corrected OR obtained from the bias correction approach and found it to be normally distributed under the null hypothesis. On the basis of the simulation study results, we found that the logistic regression approaches that adjust or do not adjust for the primary disease status had low power for detecting secondary phenotype associated variants and highly inflated type I error probabilities, whereas our approach was more powerful for identifying the SNP-secondary phenotype associations and had better-controlled type I error probabilities.
Odds ratio; bias; type I error; power; secondary phenotype; frequency-matched study; SNP; genome-wide association study
A mediation model explores the direct and indirect effects between an independent variable and a dependent variable by including other variables (or mediators). Mediation analysis has recently been used to dissect the direct and indirect effects of genetic variants on complex diseases using case-control studies. However, bias could arise in the estimations of the genetic variant-mediator association because the presence or absence of the mediator in the study samples is not sampled following the principles of case-control study design. In this case, the mediation analysis using data from case-control studies might lead to biased estimates of coefficients and indirect effects. In this article, we investigated a multiple-mediation model involving a three-path mediating effect through two mediators using case-control study data. We propose an approach to correct bias in coefficients and provide accurate estimates of the specific indirect effects. Our approach can also be used when the original case-control study is frequency matched on one of the mediators. We employed bootstrapping to assess the significance of indirect effects. We conducted simulation studies to investigate the performance of the proposed approach, and showed that it provides more accurate estimates of the indirect effects as well as the percent mediated than standard regressions. We then applied this approach to study the mediating effects of both smoking and chronic obstructive pulmonary disease (COPD) on the association between the CHRNA5-A3 gene locus and lung cancer risk using data from a lung cancer case-control study. The results showed that the genetic variant influences lung cancer risk indirectly through all three different pathways. The percent of genetic association mediated was 18.3% through smoking alone, 30.2% through COPD alone, and 20.6% through the path including both smoking and COPD, and the total genetic variant-lung cancer association explained by the two mediators was 69.1%.
Genome-wide association (GWA) studies, where hundreds of thousands of single-nucleotide polymorphisms (SNPs) are tested simultaneously, are becoming popular for identifying disease loci for common diseases. Most commonly, a GWA study involves two stages: the first stage includes testing the association between all SNPs and the disease and the second stage includes replication of SNPs selected from the first stage to validate associations in an independent sample. The first stage is considered to be more fundamental since the second stage is contingent on the results of the first stage. Selection of SNPs from stage one for genotyping in stage two is typically based on an arbitrary threshold or controlling type I errors. These strategies can be inefficient and have potential to exclude genotyping of disease-associated SNPs in stage two. We propose an approach for selecting top SNPs that uses a strategy based on the false-negative rate (FNR). Using the FNR approach, we proposed the number of SNPs that should be selected based on the observed p-values and a pre-specified multi-testing power in the first stage. We applied our method to simulated data and a GWA study of glioma (a rare form of brain tumor) data. Results from simulation and the glioma GWA indicate that the proposed approach provides an FNR-based way to select SNPs using pre-specified power.
False negative rate; SNP selection; Two-stage genome-wide association study
We previously showed that select cytokine gene polymorphisms are a significant predictor for pain reported at initial presentation in 446 white patients newly diagnosed with non–small cell lung cancer. This follow-up study explores the extent to which polymorphisms in tumor necrosis factor-α (TNF- α-308 G/A), interleukin (IL)-6 −174G/C, and IL-8 −251T/A could explain variability in pain and analgesic response among those patients (n = 140) subsequently referred for pain treatment.
Pain severity (0, no pain; 10, worst pain) was assessed at initial consultation and at follow-up visit. The total dose of opioids at the time of first-follow up visit (30 days postconsult) was converted to an equivalent dose of parenteral morphine.
Forty-one percent (57 of 140) of the patients reported severe pain (score >7/10) at initial consultation (mean, 5.5), which significantly decreased to 25% (mean, 4) at first follow-up visit (McNemar = P < 0.001). Polymorphisms in TNF and IL-6 were significantly associated with pain severity (for TNF GG, 4.12; GA, 5.38; AA, 5.50; P = 0.04) and with morphine equivalent daily dose (IL-6 GG, 69.61; GC, 73.17; CC, 181.67; P = 0.004), respectively. Adjusting for demographic and clinical variables, variant alleles in TNFα −308 G/A remained significantly associated with pain severity (b = 0.226; P = 0.036) and carriers of the IL-6 −174C/C genotypes required 4.7 times higher dose of opioids for pain relief (odds ratio, 4.7; 95% confidence interval, 1.2;15.0) relative to GG and GC genotypes.
We provide preliminary evidence of the influence of cytokine genes on pain and response to analgesia in lung cancer patients. Additional studies are needed to validate our findings. The long-term application is to tailored pain therapies.
While gliomas are the most common primary brain tumors, their etiology is largely unknown. To identify novel risk loci for glioma, we conducted genome-wide association (GWA) analysis of two case–control series from France and Germany (2269 cases and 2500 controls). Pooling these data with previously reported UK and US GWA studies provided data on 4147 glioma cases and 7435 controls genotyped for 424 460 common tagging single-nucleotide polymorphisms. Using these data, we demonstrate two statistically independent associations between glioma and rs11979158 and rs2252586, at 7p11.2 which encompasses the EGFR gene (population-corrected statistics, Pc = 7.72 × 10−8 and 2.09 × 10−8, respectively). Both associations were independent of tumor subtype, and were independent of EGFR amplification, p16INK4a deletion and IDH1 mutation status in tumors; compatible with driver effects of the variants on glioma development. These findings show that variation in 7p11.2 is a determinant of inherited glioma risk.
The Human Genome Project and HapMap have led to a better appreciation of the importance of common genetic variation in determining cancer risk, created potential for predicting response to therapy, and made possible the development of targeted prevention and therapeutic interventions. Advances in molecular epidemiology can be used to explore the role of genetic variation in modulating the risk for severe and persistent symptoms, such as pain, depression, and fatigue, in patients with cancer. The same genes that are implicated in cancer risk might also be involved in the modulation of therapeutic outcomes. For example, polymorphisms in several cytokine genes are potential markers for genetic susceptibility both for cancer risk and for cancer-related symptoms. These genetic polymorphisms are stable markers and easily and reliably assayed to explore the extent to which genetic variation might prove useful in identifying patients with cancer at high-risk of symptom development. Likewise, they could identify subgroups who might benefit most from symptom intervention, and contribute to developing personalised and more effective therapies for persistent symptoms.
Telomeres play a critical role in maintaining genome integrity. Telomere shortening is associated with the risk of many aging-related diseases. Classic twin studies have shown that genetic components may contribute up to 80% of the heritability of telomere length. In the study we report here, we used a multi-stage genome-wide association study (GWAS) to identify genetic determinants of telomere length. The mean telomere length in peripheral blood leukocytes was measured by quantitative real-time polymerase chain reaction. We first analyzed 300,000 single-nucleotide polymorphisms (SNPs) in 459 healthy controls, finding 15,120 SNPs associated with telomere length at P < 0.05. We then validated these SNPs in two independent populations comprising 890 and 270 healthy controls, respectively. Four SNPs, including rs398652 on 14q21, were associated with telomere length across all three populations (pooled P-values of < 10−5). The variant alleles of these SNPs were associated with longer telomere length. We then analyzed the association of these SNPs with the risk of bladder cancer in a large case-control study. The variant allele of rs398652 was associated with a significantly reduced risk of bladder cancer (odds ratio = 0.81; 95% confidence interval, 0.67–0.97; P = 0.025), consistent with the correlation of this variant allele with longer telomeres. We then conducted a mediation analysis to examine whether the association between rs398652 and reduced bladder cancer risk is mediated by telomere length, finding that telomere length was a significant mediator of the relationship between rs398652 and bladder cancer (P = 0.013), explaining 14% of the effect. In conclusion, we found that the SNP rs398652 on 14q21 was associated with longer telomere length and a reduced risk of bladder cancer and that a portion of the effect of this SNP on bladder cancer risk was mediated by telomere length.
SNP; telomere length; GWAS; bladder cancer risk
Genetic association studies for binary diseases are designed as case-control studies: the cases are those affected with the primary disease and the controls are free of the disease. At the time of case-control collection, information about secondary phenotypes is also collected. Association studies of secondary phenotype and genetic variants have received a great deal of interest recently. To study the secondary phenotypes, investigators use standard regression approaches, where individuals with secondary phenotypes are coded as cases and those without secondary phenotypes are coded as controls. However, using the secondary phenotype as an outcome variable in a case-control study might lead to a biased estimate of odds ratios (ORs) for genetic variants. The secondary phenotype is associated with the primary disease; therefore, individuals with and without the secondary phenotype are not sampled following the principles of a case-control study. In this article, we demonstrate that such analyses will lead to a biased estimate of OR and propose new approaches to provide more accurate OR estimates of genetic variants associated with the secondary phenotype for both unmatched and frequency-matched (with respect to the secondary phenotype) case-control studies. We also propose a bootstrapping method to estimate the empirical confidence intervals for the corrected ORs. Using simulation studies and analysis of lung cancer data for single-nucleotide polymorphism associated with smoking quantity, we compared our new approaches to standard logistic regression and to an extended version of the inverse-probability-of-sampling-weighted regression. The proposed approaches provide more accurate estimation of the true OR.
Odds ratio; bias; secondary phenotype; un-matched and frequency-matched study; SNP; genome-wide association study
To examine factors associated with ever use of alcohol among Mexican origin youth.
Using a prospective study design, we followed 1053 Mexican origin adolescents. Participants completed two surveys in their homes and three follow-up telephone interviews, every six to eight months, in between. The second home survey was completed 30 months (SD=4.8 months) after baseline. Acculturation, subjective social status, and family cohesion were assessed at baseline and final home visit. Ever drinking, risk behaviors, and sensation seeking tendencies were assessed at the final home visit only.
Overall, 30% of the study participants reported ever drinking alcohol. Multivariate models revealed that being female, increasing age, lower levels of acculturation, family cohesion and subjective social status, higher sensation seeking tendencies and concomitantly engaging in three or four other risk behaviors were associated with ever drinking. Also, social disinhibition, an aspect of sensation seeking, mediated the relationship between engaging in other risk behaviors and alcohol use. This is consistent with previous research, suggesting that social disinhibition is a common factor that underlies the use of alcohol, tobacco, illicit drugs, and other problem behaviors.
The results of this study support taking a family-based approach to prevention that includes discussion of other risk behaviors, especially smoking, among Mexican origin youth. In addition, tailoring programs by gender, directly addressing both how changes in social norms resulting from acculturation can impact a youth’s decision to drink alcohol and underlying gender-based differences in why youth drink could improve the efficacy of preventive interventions.
In case-control genetic association studies, cases are subjects with the disease and controls are subjects without the disease. At the time of case-control data collection, information about secondary phenotypes is also collected. In addition to studies of primary diseases, there has been some interest in studying genetic variants associated with secondary phenotypes. In genetic association studies, the deviation from Hardy-Weinberg proportion (HWP) of each genetic marker is assessed as an initial quality check to identify questionable genotypes. Generally, HWP tests are performed based on the controls for the primary disease or secondary phenotype. However, when the disease or phenotype of interest is common, the controls do not represent the general population. Therefore, using only controls for testing HWP can result in a highly inflated type I error rate for the disease- and/or phenotype-associated variants. Recently, two approaches, the likelihood ratio test (LRT) approach and the mixture HWP (mHWP) exact test were proposed for testing HWP in samples from case-control studies. Here, we show that these two approaches result in inflated type I error rates and could lead to the removal from further analysis of potential causal genetic variants associated with the primary disease and/or secondary phenotype when the study of primary disease is frequency-matched on the secondary phenotype. Therefore, we proposed alternative approaches, which extend the LRT and mHWP approaches, for assessing HWP that account for frequency matching. The goal was to maintain more (possible causative) single-nucleotide polymorphisms in the sample for further analysis. Our simulation results showed that both extended approaches could control type I error probabilities. We also applied the proposed approaches to test HWP for SNPs from a genome-wide association study of lung cancer that was frequency-matched on smoking status and found that the proposed approaches can keep more genetic variants for association studies.
Background: DNA strand breaks pose the greatest threat to genomic stability. Genetically determined mutagen sensitivity predisposes individuals to a variety of cancers, including glioma. However, polymorphisms in DNA strand break repair genes that may determine mutagen sensitivity are not well studied in cancer risk, especially in gliomas.
Methods: We correlated genotype data for tag single-nucleotide polymorphisms (tSNPs) of DNA strand break repair genes with a gamma-radiation-induced mutagen sensitivity phenotype [expressed as mean breaks per cell (B/C)] in samples from 426 glioma patients. We also conducted analysis to assess joint and haplotype effects of single-nucleotide polymorphisms (SNPs) on mutagen sensitivity. We further validate our results in an independent external control group totaling 662 subjects.
Results: Of the 392 tSNPs examined, we found that mutagen sensitivity was modified by one tSNP in the EME2 gene and six tSNPs in the RAD51L1 gene (P < 0.01). Among the six RAD51L1 SNPs tested in the validation set, one (RAD51L1 rs2180611) was significantly associated with mutagen sensitivity (P = 0.025). Moreover, we found a significant dose–response relationship between the mutagen sensitivity and the number of adverse tSNP genotypes. Furthermore, haplotype analysis revealed that RAD51L1 haplotypes F-A (zero adverse allele) and F-E (six adverse alleles) exhibited the lowest (0.42) and highest (0.93) mean B/C values, respectively. A similar dose–response relationship also existed between the mutagen sensitivity and the number of adverse haplotypes.
Conclusion: These results suggest that polymorphisms in and haplotypes of the RAD51L1 gene, which is involved in the double-strand break repair pathway, modulate gamma-radiation-induced mutagen sensitivity.
Recent genome-wide association (GWA) studies of lung cancer have shown that the CHRNA5-A3 region on chromosome 15q24-25.1 is strongly associated with an increased risk of lung cancer and nicotine dependence, and thought to be associated with chronic obstructive airways disease as well. However, it has not been established whether the association between genetic variants and lung cancer risk is a direct one or one mediated by nicotine dependence.
In this paper we applied a rigorous statistical approach, mediation analysis, to examine the mediating effect of smoking behavior and self-reported physician-diagnosed emphysema (chronic obstructive pulmonary disease [COPD]) on the relationship between the CHRNA5-A3 region genetic variant rs1051730 and the risk of lung cancer.
Our results showed that rs1051730 is directly associated with lung cancer risk, but that it is also associated with lung cancer risk through its effect on both smoking behavior and COPD. Furthermore, we showed that COPD is a mediating phenotype that explains part of the effect of smoking behavior on lung cancer. Our results also suggested that smoking behavior is a mediator of the relationship between rs1051730 and COPD risk.
Smoking behavior and COPD are mediators of the association between the SNP rs1051730 and the risk of lung cancer. Also, COPD is a mediator of the association between smoking behavior and lung cancer. Finally, smoking behavior also has mediating effects on the association between the SNP and COPD.
Lung Cancer; COPD; Mediation analysis; smoking behavior; genetic variants
As genome-wide association studies expand beyond populations of European ancestry, the role of admixture will become increasingly important in the continued discovery and fine-mapping of variation influencing complex traits. Although admixture is commonly viewed as a confounding influence in association studies, approaches such as admixture mapping have demonstrated its ability to highlight disease susceptibility regions of the genome. In this study, we illustrate a powerful two-stage testing strategy designed to uncover trait-associated single nucleotide polymorphisms in the presence of ancestral allele frequency differentiation. In the first stage, we conduct an association scan by using predicted genotypic values based on regional admixture estimates. We then select a subset of promising markers for inclusion in a second-stage analysis, where association is tested between the observed genotype and the phenotype conditional on the predicted genotype. We prove that, under the null hypothesis, the test statistics used in each stage are orthogonal and asymptotically independent. Using simulated data designed to mimic African-American populations in the case of a quantitative trait, we show that our two-stage procedure maintains appropriate control of the family wise error rate and has higher power under realistic effect sizes than the one-stage testing procedure in which all markers are tested for association simultaneously with control of admixture. We apply the proposed procedure to a study of height in 201 African-Americans genotyped at 108 ancestry informative markers. The two-stage procedure identified two statistically significant markers rs1985080 (PTHB1/BBS9) and rs952718 (ABCA12). PTHB1/BBS9 is downregulated by parathyroid hormone in osteoblastic cells and is thought to be involved in parathyroid hormone action in bones and may play a role in height. ABCA12 is a member of the superfamily of ATP-binding cassette transporters and its potential involvement in height is unclear.
two-stage; structured association testing; admixture mapping; regional admixture estimate; genome-wide association studies
Recent advances in human genome studies have opened new avenues for the identification of susceptibility genes for many complex genetic disorders, especially in the field of rare cancers such as glioma. To date, eight glioma susceptibility loci have been identified by candidate gene-association studies: PRKDC G6721T, XRCC1 W399R, PARP1 A762V, MGMT F84L, ERCC1 A8092C, ERCC2 Q751K, EGF +61 A/G and IL13 R110G. Five loci have been identified by genome-wide association studies: TERT rs2736100, CCDC26 rs4295627, CDKN2A–CDKN2B rs4977756, PHLDB1 rs498872, and RTEL1 rs6010620. Using the Ingenuity Pathway Analysis tool, we investigated whether these 13 susceptibility genes are biologically related. Our data provide not only networks for understanding the biological properties of gliomagenesis but useful pathway maps for future understanding of disease.
Glioma; Susceptibility; Pathway analysis
Glioblastoma (GBM) is the most common and aggressive type of glioma and has the poorest survival. However, a small percentage of patients with GBM survive well beyond the established median. Therefore, identifying the genetic variants that influence this small number of unusually long-term survivors may provide important insight into tumor biology and treatment.
Patients and Methods
Among 590 patients with primary GBM, we evaluated associations of survival with the 100 top-ranking glioma susceptibility single nucleotide polymorphisms from our previous genome-wide association study using Cox regression models. We also compared differences in genetic variation between short-term survivors (STS; ≤ 12 months) and long-term survivors (LTS; ≥ 36 months), and explored classification and regression tree analysis for survival data. We tested results using two independent series totaling 543 GBMs.
We identified LIG4 rs7325927 and BTBD2 rs11670188 as predictors of STS in GBM and CCDC26 rs10464870 and rs891835, HMGA2 rs1563834, and RTEL1 rs2297440 as predictors of LTS. Further survival tree analysis revealed that patients ≥ 50 years old with LIG4 rs7325927 (V) had the worst survival (median survival time, 1.2 years) and exhibited the highest risk of death (hazard ratio, 17.53; 95% CI, 4.27 to 71.97) compared with younger patients with combined RTEL1 rs2297440 (V) and HMGA2 rs1563834 (V) genotypes (median survival time, 7.8 years).
Polymorphisms in the LIG4, BTBD2, HMGA2, and RTEL1 genes, which are involved in the double-strand break repair pathway, are associated with GBM survival.
Neuropathic pain (NP) is a debilitating symptom experienced by a number of patients with cancer. We evaluated the validity of ID Pain as a screening tool for NP in breast cancer survivors using the S-LANSS and a reported diagnosis of NP as criterion measures. Two hundred and forty breast cancer survivors with a mean age of 58 years (SD= 16) participated in this survey. Forty-five percent of the sample reported having pain in the past week. Of those reporting pain, 33% reported that they had been diagnosed by their health care provider for NP, 39% had a positive ID Pain (≥ 2) score and 19% had a positive S-LANSS score. The most commonly endorsed ID Pain item was “hot/burning” (n = 48), followed by feeling “numb” (n = 47) and “pins and needles” (n = 45). Total ID Pain score was significantly associated with a clinical diagnosis of NP (r = 0.41; P < 0.001) and the S-LANSS total score (r = 0.54; P < 0.001). Receiver Operating Curve analysis demonstrated that ID Pain has a predictive validity of 0.72 and 0.70 for diagnosis of NP as made by clinicians and the S-LANSS, respectively. We also found that an ID Pain score of ≥ 2 corresponded with the likelihood of NP in this sample, consistent with the original ID Pain development study. This study provides evidence for ID Pain as a valid screening measure of NP for breast cancer survivors.
Neuropathic pain; ID Pain; epidemiology; breast cancer; symptoms; survivorship
As genome-wide association studies expand beyond populations of European ancestry, the role of admixture will become increasingly important in the continued discovery and fine-mapping of variation influencing complex traits. Although admixture is commonly viewed as a confounding influence in association studies, approaches such as admixture mapping have demonstrated its ability to highlight disease susceptibility regions of the genome. In this study, we illustrate a powerful two-stage testing strategy designed to uncover trait-associated single nucleotide polymorphisms in the presence of ancestral allele frequency differentiation. In the first stage, we conduct an association scan by using predicted genotypic values based on regional admixture estimates. We then select a subset of promising markers for inclusion in a second-stage analysis, where association is tested between the observed genotype and the phenotype conditional on the predicted genotype. We prove that, under the null hypothesis, the test statistics used in each stage are orthogonal and asymptotically independent. Using simulated data designed to mimic African-American populations in the case of a quantitative trait, we show that our two-stage procedure maintains appropriate control of the family wise error rate and has higher power under realistic effect sizes than the one-stage testing procedure in which all markers are tested for association simultaneously with control of admixture. We apply the proposed procedure to a study of height in 201 African-Americans genotyped at 108 ancestry informative markers. The two-stage procedure identified two statistically significant markers rs1985080 (PTHB1/BBS9) and rs952718 (ABCA12). PTHB1/BBS9 is downregulated by parathyroid hormone in osteoblastic cells and is thought to be involved in parathyroid hormone action in bones and may play a role in height. ABCA12 is a member of the superfamily of ATP binding cassette transporters and its potential involvement in height is unclear.
two-stage; structured association testing; admixture mapping; regional admixture estimate; genome-wide association studies